A vendor may target specific consumers, in a population of consumers, to address individualized marketplace needs. For example, a vendor may provide promotions customized for certain potential customers. Such promotional content (e.g. advertisements) may be uniquely tailored to different consumers. Personalizing promotional content for electronic delivery can lead to an increase in revenues, but there are some shortcomings. For example, marketing to address singular customer needs may be overly burdensome, time consuming, infeasible due to scalability, and expensive.
Consumer needs and wants may overlap with other needs and wants. Marketing based on dividing a prospective consumer audience into discrete categories representative of a particular defining characteristic can be beneficial. For example, clustering based on select behavioral data, demographic data, and product preferences may improve efficiency and reduce cost. Segmentation according to these conventional categories, however, may deprive a marketer of the benefits of marketing by category. For example, two consumers of the same age may receive the same advertisement because they are categorized in the same manner based on age. However, these consumers may be at different stages of their lives and thus have different motivations or values. This can lead to one consumer in the category enthusiastically purchasing the advertised product while the other consumer is vehemently opposed to purchasing the product. Segmenting these two consumers solely on a single basis (e.g., age) can be inefficient and ineffective.
Conventional segmentation techniques may also cause privacy and security concerns. For example, it is common for conventional systems to identify consumers using identifiers or information that includes personal identifiable information (e.g., name, email address, phone number or the like). It is also common for conventional systems to exchange these identifiers over communication networks. This can lead to data leaks or losses that can potential expose personal identifiable information of the consumers to attackers or other unauthorized users. Furthermore, attackers (e.g., hackers) can use the personal identifiable information obtained from one attack against the same or additional consumers in subsequent attacks (e.g., using techniques such as phishing, social engineering or the like).
Therefore, there is a need for an improved method of providing people-based audience planning and targeted advertising.